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Predictors of malignancy in incidental adnexal lesions identified on CT in patients with prior non-ovarian cancer

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Abstract

Purpose

To identify imaging features in incidental adnexal lesions which are associated with malignancy on portal venous phase contrast-enhanced CT in patients with known non-ovarian cancer.

Materials and methods

This IRB-approved, HIPAA-compliant retrospective study was performed at a tertiary cancer center. Portal venous phase contrast-enhanced CT from January 2010 to December 2015 was reviewed to identify women with non-ovarian malignancy and incidental adnexal lesion, with mean 18 months (range 1–80 months) to definitive diagnosis or last imaging follow-up. Imaging features of adnexal lesions were recorded (size, laterality, shape, attenuation, and composition) and correlated with outcome (benign or malignant) using univariate and multivariate logistic regression analysis. A point-based system was used to predict likelihood of malignancy.

Results

Of 276 women (mean age 45 years), 216 (78.3%) had benign lesions, 58 (21.0%) ovarian metastasis, and 2 (0.7%) had primary ovarian malignancy. On logistic regression model, lesion size > 5 cm (p-value, OR, 95% CI 0.01, 9.11, 1.70–48.87), bilaterality (< 0.0001, 28.34, 7.46–107.67), irregular shape (0.01, 12.31, 1.61–94.05), higher-than-simple-fluid attenuation (< 0.0001, 28.27, 5.65–141.59), and heterogeneous composition (0.0017, 10.75, 2.45–47.23) were associated with malignant outcome (AUC 0.97). A point-based system incorporating these five features (possible 0–5 points) had AUC of 0.97. Rate of malignancy was 0% (0/147) if none of the features of malignancy were present, 12.7% (8/63) if one feature was present, 51.7% (15/29) if two features were present, and 100% (37/37) if three or more features present.

Conclusion

Risk of malignancy of incidental adnexal lesions in women with prior non-ovarian cancer can be estimated based on lesion features seen on portal venous phase contrast-enhanced CT.

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Abbreviations

ACR:

American College of Radiology

AUC:

Area under the ROC curve

NLP:

Natural language processing

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Authors and Affiliations

  1. Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA, 02115, USA

    Atul B. Shinagare, Isha Gujrathi, Laila Cochon, Kristine S. Burk & Ramin Khorasani

  2. Department of Radiology, Harvard Medical School, Brigham and Women’s Hospital, 75 Francis St, Boston, MA, 02115, USA

    Atul B. Shinagare, Isha Gujrathi, Laila Cochon, Kristine S. Burk & Ramin Khorasani

  3. Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA

    Atul B. Shinagare, Kristine S. Burk & Ramin Khorasani

  4. Department of Radiology and Department of Obstetrics and Gynecology, University of Wisconsin, Madison, WI, USA

    Elizabeth Sadowski

Authors
  1. Atul B. Shinagare
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  2. Isha Gujrathi
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Correspondence to Atul B. Shinagare.

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Atul Shinagare does not have any conflict of interest relevant to this work and declares that he is a consultant for Arog Pharmaceuticals and Imaging Endpoints.

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Shinagare, A.B., Gujrathi, I., Cochon, L. et al. Predictors of malignancy in incidental adnexal lesions identified on CT in patients with prior non-ovarian cancer. Abdom Radiol 47, 320–327 (2022). https://doi.org/10.1007/s00261-021-03233-2

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  • DOI: https://doi.org/10.1007/s00261-021-03233-2

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